Overview

Dataset statistics

Number of variables22
Number of observations160
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.6 KiB
Average record size in memory176.8 B

Variable types

Categorical6
Numeric15
Unsupported1

Alerts

How many social media platforms are you on? has a high cardinality: 64 distinct valuesHigh cardinality
Enter Marks(percentage) For 10th Grade: is highly overall correlated with Department:High correlation
Time spend on Facebook? (In hours) is highly overall correlated with How many social media platforms are you on?High correlation
Time spend on Pinterest? (In hours) is highly overall correlated with Time spend on Reddit? (In hours)High correlation
Time spend on Twitter? (In hours) is highly overall correlated with How many social media platforms are you on? and 1 other fieldsHigh correlation
Overall time spent on other application? (In hours) is highly overall correlated with How many social media platforms are you on?High correlation
Department: is highly overall correlated with Enter Marks(percentage) For 10th Grade: and 1 other fieldsHigh correlation
Choose Current year: is highly overall correlated with Department:High correlation
How many social media platforms are you on? is highly overall correlated with Time spend on Facebook? (In hours) and 3 other fieldsHigh correlation
Time spend on Reddit? (In hours) is highly overall correlated with Time spend on Pinterest? (In hours) and 2 other fieldsHigh correlation
Time spend on Reddit? (In hours) is highly imbalanced (87.8%)Imbalance
Time spend on Discord? (In hours) is an unsupported type, check if it needs cleaning or further analysisUnsupported
How often do you use social media ? (In hours) has 5 (3.1%) zerosZeros
Time spent on WhatsApp? (In hours) has 3 (1.9%) zerosZeros
Time spend on Instagram? (In hours) has 37 (23.1%) zerosZeros
Time spend on Facebook? (In hours) has 147 (91.9%) zerosZeros
Time spend on YouTube? (In hours) has 12 (7.5%) zerosZeros
Time spend on Snapchat? (In hours) has 62 (38.8%) zerosZeros
Time spend on Pinterest? (In hours) has 134 (83.8%) zerosZeros
Time spend on Twitter? (In hours) has 136 (85.0%) zerosZeros
Time spend on Telegram? (In hours) has 131 (81.9%) zerosZeros
Overall time spent on other application? (In hours) has 34 (21.2%) zerosZeros
What is the maximum time that you have spent away from your phone? (In hours) has 3 (1.9%) zerosZeros
Entertainment usage time while using phone(per day) (In hours) has 4 (2.5%) zerosZeros
Productivity and finance time while using phone (per day)(In hours) has 22 (13.8%) zerosZeros

Reproduction

Analysis started2023-04-06 22:37:55.559635
Analysis finished2023-04-06 22:40:47.609798
Duration2 minutes and 52.05 seconds
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

Department:
Categorical

Distinct6
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Computer
91 
Artificial Intelligence
32 
Electronics
23 
Information Technology
 
7
Electrical
 
4

Length

Max length23
Median length8
Mean length12.13125
Min length8

Characters and Unicode

Total characters1941
Distinct characters24
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowComputer
2nd rowInformation Technology
3rd rowInformation Technology
4th rowInformation Technology
5th rowElectronics

Common Values

ValueCountFrequency (%)
Computer 91
56.9%
Artificial Intelligence 32
 
20.0%
Electronics 23
 
14.4%
Information Technology 7
 
4.4%
Electrical 4
 
2.5%
Mechanical 3
 
1.9%

Length

2023-04-07T04:10:47.899719image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-07T04:10:48.041175image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
computer 91
45.7%
artificial 32
 
16.1%
intelligence 32
 
16.1%
electronics 23
 
11.6%
information 7
 
3.5%
technology 7
 
3.5%
electrical 4
 
2.0%
mechanical 3
 
1.5%

Most occurring characters

ValueCountFrequency (%)
e 224
11.5%
t 189
 
9.7%
i 165
 
8.5%
r 157
 
8.1%
o 142
 
7.3%
l 137
 
7.1%
c 131
 
6.7%
n 111
 
5.7%
m 98
 
5.0%
C 91
 
4.7%
Other values (14) 496
25.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1703
87.7%
Uppercase Letter 199
 
10.3%
Space Separator 39
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 224
13.2%
t 189
11.1%
i 165
9.7%
r 157
9.2%
o 142
8.3%
l 137
8.0%
c 131
7.7%
n 111
6.5%
m 98
 
5.8%
p 91
 
5.3%
Other values (7) 258
15.1%
Uppercase Letter
ValueCountFrequency (%)
C 91
45.7%
I 39
19.6%
A 32
 
16.1%
E 27
 
13.6%
T 7
 
3.5%
M 3
 
1.5%
Space Separator
ValueCountFrequency (%)
39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1902
98.0%
Common 39
 
2.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 224
11.8%
t 189
9.9%
i 165
 
8.7%
r 157
 
8.3%
o 142
 
7.5%
l 137
 
7.2%
c 131
 
6.9%
n 111
 
5.8%
m 98
 
5.2%
C 91
 
4.8%
Other values (13) 457
24.0%
Common
ValueCountFrequency (%)
39
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1941
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 224
11.5%
t 189
 
9.7%
i 165
 
8.5%
r 157
 
8.1%
o 142
 
7.3%
l 137
 
7.1%
c 131
 
6.7%
n 111
 
5.7%
m 98
 
5.0%
C 91
 
4.7%
Other values (14) 496
25.6%
Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
First year
64 
Second year
49 
Third year
47 

Length

Max length11
Median length10
Mean length10.30625
Min length10

Characters and Unicode

Total characters1649
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSecond year
2nd rowFirst year
3rd rowSecond year
4th rowSecond year
5th rowThird year

Common Values

ValueCountFrequency (%)
First year 64
40.0%
Second year 49
30.6%
Third year 47
29.4%

Length

2023-04-07T04:10:48.171618image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-07T04:10:48.293727image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
year 160
50.0%
first 64
 
20.0%
second 49
 
15.3%
third 47
 
14.7%

Most occurring characters

ValueCountFrequency (%)
r 271
16.4%
e 209
12.7%
160
9.7%
y 160
9.7%
a 160
9.7%
i 111
 
6.7%
d 96
 
5.8%
F 64
 
3.9%
s 64
 
3.9%
t 64
 
3.9%
Other values (6) 290
17.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1329
80.6%
Space Separator 160
 
9.7%
Uppercase Letter 160
 
9.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 271
20.4%
e 209
15.7%
y 160
12.0%
a 160
12.0%
i 111
8.4%
d 96
 
7.2%
s 64
 
4.8%
t 64
 
4.8%
c 49
 
3.7%
o 49
 
3.7%
Other values (2) 96
 
7.2%
Uppercase Letter
ValueCountFrequency (%)
F 64
40.0%
S 49
30.6%
T 47
29.4%
Space Separator
ValueCountFrequency (%)
160
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1489
90.3%
Common 160
 
9.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 271
18.2%
e 209
14.0%
y 160
10.7%
a 160
10.7%
i 111
7.5%
d 96
 
6.4%
F 64
 
4.3%
s 64
 
4.3%
t 64
 
4.3%
S 49
 
3.3%
Other values (5) 241
16.2%
Common
ValueCountFrequency (%)
160
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1649
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 271
16.4%
e 209
12.7%
160
9.7%
y 160
9.7%
a 160
9.7%
i 111
 
6.7%
d 96
 
5.8%
F 64
 
3.9%
s 64
 
3.9%
t 64
 
3.9%
Other values (6) 290
17.6%
Distinct94
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.837813
Minimum49
Maximum98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-04-07T04:10:48.409104image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum49
5-th percentile61.9
Q178.55
median85.9
Q389.4
95-th percentile94.543
Maximum98
Range49
Interquartile range (IQR)10.85

Descriptive statistics

Standard deviation9.730919
Coefficient of variation (CV)0.11746953
Kurtosis1.211239
Mean82.837813
Median Absolute Deviation (MAD)5.2
Skewness-1.1858192
Sum13254.05
Variance94.690784
MonotonicityNot monotonic
2023-04-07T04:10:48.540757image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
88 7
 
4.4%
80 5
 
3.1%
89 5
 
3.1%
90.6 5
 
3.1%
85 5
 
3.1%
80.2 4
 
2.5%
87 4
 
2.5%
89.2 3
 
1.9%
92 3
 
1.9%
86.4 3
 
1.9%
Other values (84) 116
72.5%
ValueCountFrequency (%)
49 1
0.6%
52 1
0.6%
56 1
0.6%
57 2
1.2%
59.78 1
0.6%
60 2
1.2%
62 1
0.6%
63.8 1
0.6%
64.6 1
0.6%
65 2
1.2%
ValueCountFrequency (%)
98 1
0.6%
96.6 1
0.6%
95.5 1
0.6%
95.2 2
1.2%
95 2
1.2%
94.6 1
0.6%
94.54 1
0.6%
94 2
1.2%
93.8 2
1.2%
93.4 1
0.6%
Distinct103
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.319875
Minimum19
Maximum92.84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-04-07T04:10:48.681214image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile60
Q172.9325
median79.07
Q383.85
95-th percentile89.7365
Maximum92.84
Range73.84
Interquartile range (IQR)10.9175

Descriptive statistics

Standard deviation9.845498
Coefficient of variation (CV)0.12733463
Kurtosis6.9502292
Mean77.319875
Median Absolute Deviation (MAD)5.115
Skewness-1.7571718
Sum12371.18
Variance96.93383
MonotonicityNot monotonic
2023-04-07T04:10:48.822837image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80 8
 
5.0%
75 6
 
3.8%
86 5
 
3.1%
78 5
 
3.1%
82 5
 
3.1%
60 4
 
2.5%
79 4
 
2.5%
74 3
 
1.9%
70 3
 
1.9%
73 3
 
1.9%
Other values (93) 114
71.2%
ValueCountFrequency (%)
19 1
 
0.6%
52 1
 
0.6%
53 1
 
0.6%
54.87 1
 
0.6%
56.9 1
 
0.6%
57 1
 
0.6%
60 4
2.5%
61.2 1
 
0.6%
61.57 1
 
0.6%
61.6 1
 
0.6%
ValueCountFrequency (%)
92.84 1
 
0.6%
91.89 3
1.9%
91.78 1
 
0.6%
90 2
1.2%
89.86 1
 
0.6%
89.73 1
 
0.6%
89.44 1
 
0.6%
89 3
1.9%
88.89 1
 
0.6%
88.87 1
 
0.6%
Distinct22
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.75425
Minimum0
Maximum24
Zeros5
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-04-07T04:10:48.958163image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.975
Q12
median3
Q34
95-th percentile10
Maximum24
Range24
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.4911456
Coefficient of variation (CV)0.92991825
Kurtosis10.283666
Mean3.75425
Median Absolute Deviation (MAD)1
Skewness2.8285664
Sum600.68
Variance12.188098
MonotonicityNot monotonic
2023-04-07T04:10:49.074761image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2 44
27.5%
3 32
20.0%
4 20
12.5%
1 15
 
9.4%
5 10
 
6.2%
6 8
 
5.0%
0 5
 
3.1%
7 4
 
2.5%
10 4
 
2.5%
15 3
 
1.9%
Other values (12) 15
 
9.4%
ValueCountFrequency (%)
0 5
 
3.1%
0.5 3
 
1.9%
1 15
 
9.4%
1.2 1
 
0.6%
1.5 1
 
0.6%
2 44
27.5%
2.5 1
 
0.6%
3 32
20.0%
3.5 1
 
0.6%
4 20
12.5%
ValueCountFrequency (%)
24 1
 
0.6%
18 1
 
0.6%
17 1
 
0.6%
15 3
 
1.9%
12 1
 
0.6%
10 4
2.5%
9 1
 
0.6%
8 2
 
1.2%
7 4
2.5%
6 8
5.0%
Distinct12
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Educational, Entertainment, Research/Reading, Gaming
35 
Educational, Entertainment, Research/Reading
27 
Entertainment
26 
Educational, Entertainment
25 
Educational
17 
Other values (7)
30 

Length

Max length52
Median length39
Mean length31.1125
Min length6

Characters and Unicode

Total characters4978
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.6%

Sample

1st rowEducational, Entertainment, Research/Reading, Gaming
2nd rowEducational, Entertainment, Research/Reading, Gaming
3rd rowEducational, Entertainment, Research/Reading
4th rowEntertainment
5th rowEducational, Entertainment

Common Values

ValueCountFrequency (%)
Educational, Entertainment, Research/Reading, Gaming 35
21.9%
Educational, Entertainment, Research/Reading 27
16.9%
Entertainment 26
16.2%
Educational, Entertainment 25
15.6%
Educational 17
10.6%
Educational, Entertainment, Gaming 10
 
6.2%
Entertainment, Research/Reading 6
 
3.8%
Educational, Research/Reading 4
 
2.5%
Gaming 4
 
2.5%
Research/Reading 3
 
1.9%
Other values (2) 3
 
1.9%

Length

2023-04-07T04:10:49.183163image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
entertainment 132
34.9%
educational 118
31.2%
research/reading 76
20.1%
gaming 52
 
13.8%

Most occurring characters

ValueCountFrequency (%)
n 642
12.9%
a 572
11.5%
t 514
 
10.3%
e 492
 
9.9%
i 378
 
7.6%
E 250
 
5.0%
218
 
4.4%
, 218
 
4.4%
r 208
 
4.2%
d 194
 
3.9%
Other values (11) 1292
26.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4012
80.6%
Uppercase Letter 454
 
9.1%
Other Punctuation 294
 
5.9%
Space Separator 218
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 642
16.0%
a 572
14.3%
t 514
12.8%
e 492
12.3%
i 378
9.4%
r 208
 
5.2%
d 194
 
4.8%
c 194
 
4.8%
m 184
 
4.6%
g 128
 
3.2%
Other values (5) 506
12.6%
Uppercase Letter
ValueCountFrequency (%)
E 250
55.1%
R 152
33.5%
G 52
 
11.5%
Other Punctuation
ValueCountFrequency (%)
, 218
74.1%
/ 76
 
25.9%
Space Separator
ValueCountFrequency (%)
218
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4466
89.7%
Common 512
 
10.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 642
14.4%
a 572
12.8%
t 514
11.5%
e 492
11.0%
i 378
8.5%
E 250
 
5.6%
r 208
 
4.7%
d 194
 
4.3%
c 194
 
4.3%
m 184
 
4.1%
Other values (8) 838
18.8%
Common
ValueCountFrequency (%)
218
42.6%
, 218
42.6%
/ 76
 
14.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4978
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 642
12.9%
a 572
11.5%
t 514
 
10.3%
e 492
 
9.9%
i 378
 
7.6%
E 250
 
5.0%
218
 
4.4%
, 218
 
4.4%
r 208
 
4.2%
d 194
 
3.9%
Other values (11) 1292
26.0%

How many social media platforms are you on?
Categorical

HIGH CARDINALITY  HIGH CORRELATION 

Distinct64
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
WhatsApp, Instagram, YouTube, Snapchat
28 
WhatsApp, YouTube
14 
WhatsApp, Instagram, YouTube
13 
WhatsApp, Instagram, YouTube, Snapchat, Pinterest
WhatsApp, YouTube, Snapchat
 
8
Other values (59)
88 

Length

Max length109
Median length87
Mean length43.8375
Min length7

Characters and Unicode

Total characters7014
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)26.9%

Sample

1st rowWhatsApp, Instagram, YouTube, Snapchat
2nd rowWhatsApp, Instagram, Facebook, YouTube, Snapchat, Discord, Twitter
3rd rowWhatsApp, Instagram, Facebook, YouTube, Snapchat, Discord, Twitter,
4th rowWhatsApp, Instagram, YouTube, Snapchat, Discord, Pinterest
5th rowWhatsApp, YouTube, Snapchat, Pinterest, Twitter

Common Values

ValueCountFrequency (%)
WhatsApp, Instagram, YouTube, Snapchat 28
17.5%
WhatsApp, YouTube 14
 
8.8%
WhatsApp, Instagram, YouTube 13
 
8.1%
WhatsApp, Instagram, YouTube, Snapchat, Pinterest 9
 
5.6%
WhatsApp, YouTube, Snapchat 8
 
5.0%
WhatsApp, Instagram, Facebook, YouTube, Snapchat 5
 
3.1%
WhatsApp, YouTube, Telegram 4
 
2.5%
WhatsApp, Instagram, YouTube, Snapchat, Telegram 4
 
2.5%
WhatsApp, Instagram, YouTube, Snapchat, Twitter 4
 
2.5%
WhatsApp, Instagram, YouTube, Snapchat, Pinterest, Twitter, Telegram 4
 
2.5%
Other values (54) 67
41.9%

Length

2023-04-07T04:10:49.308769image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
whatsapp 157
21.2%
youtube 150
20.3%
instagram 123
16.6%
snapchat 112
15.1%
telegram 49
 
6.6%
pinterest 38
 
5.1%
twitter 38
 
5.1%
facebook 29
 
3.9%
discord 28
 
3.8%
reddit 11
 
1.5%
Other values (5) 5
 
0.7%

Most occurring characters

ValueCountFrequency (%)
a 706
 
10.1%
592
 
8.4%
, 591
 
8.4%
t 558
 
8.0%
p 426
 
6.1%
e 403
 
5.7%
s 347
 
4.9%
u 300
 
4.3%
r 277
 
3.9%
n 273
 
3.9%
Other values (24) 2541
36.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4784
68.2%
Uppercase Letter 1046
 
14.9%
Space Separator 592
 
8.4%
Other Punctuation 592
 
8.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 706
14.8%
t 558
11.7%
p 426
8.9%
e 403
8.4%
s 347
 
7.3%
u 300
 
6.3%
r 277
 
5.8%
n 273
 
5.7%
h 271
 
5.7%
o 240
 
5.0%
Other values (10) 983
20.5%
Uppercase Letter
ValueCountFrequency (%)
T 239
22.8%
W 157
15.0%
A 157
15.0%
Y 150
14.3%
I 123
11.8%
S 112
10.7%
P 39
 
3.7%
F 29
 
2.8%
D 28
 
2.7%
R 11
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 591
99.8%
. 1
 
0.2%
Space Separator
ValueCountFrequency (%)
592
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5830
83.1%
Common 1184
 
16.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 706
 
12.1%
t 558
 
9.6%
p 426
 
7.3%
e 403
 
6.9%
s 347
 
6.0%
u 300
 
5.1%
r 277
 
4.8%
n 273
 
4.7%
h 271
 
4.6%
o 240
 
4.1%
Other values (21) 2029
34.8%
Common
ValueCountFrequency (%)
592
50.0%
, 591
49.9%
. 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7014
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 706
 
10.1%
592
 
8.4%
, 591
 
8.4%
t 558
 
8.0%
p 426
 
6.1%
e 403
 
5.7%
s 347
 
4.9%
u 300
 
4.3%
r 277
 
3.9%
n 273
 
3.9%
Other values (24) 2541
36.2%
Distinct18
Distinct (%)11.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.601875
Minimum0
Maximum10
Zeros3
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-04-07T04:10:49.454381image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.295
Q11
median1
Q32
95-th percentile5
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4399608
Coefficient of variation (CV)0.89892206
Kurtosis9.5066622
Mean1.601875
Median Absolute Deviation (MAD)0
Skewness2.738882
Sum256.3
Variance2.073487
MonotonicityNot monotonic
2023-04-07T04:10:49.561439image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1 86
53.8%
2 31
 
19.4%
3 9
 
5.6%
0.5 8
 
5.0%
6 5
 
3.1%
5 3
 
1.9%
0 3
 
1.9%
0.1 2
 
1.2%
0.05 2
 
1.2%
0.3 2
 
1.2%
Other values (8) 9
 
5.6%
ValueCountFrequency (%)
0 3
 
1.9%
0.05 2
 
1.2%
0.1 2
 
1.2%
0.2 1
 
0.6%
0.3 2
 
1.2%
0.5 8
 
5.0%
0.9 1
 
0.6%
1 86
53.8%
1.3 1
 
0.6%
1.5 1
 
0.6%
ValueCountFrequency (%)
10 1
 
0.6%
7 1
 
0.6%
6 5
 
3.1%
5 3
 
1.9%
4 2
 
1.2%
3 9
 
5.6%
2.5 1
 
0.6%
2 31
19.4%
1.5 1
 
0.6%
1.3 1
 
0.6%
Distinct21
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.67925
Minimum0
Maximum21
Zeros37
Zeros (%)23.1%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-04-07T04:10:49.671149image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.275
median1
Q32
95-th percentile5.05
Maximum21
Range21
Interquartile range (IQR)1.725

Descriptive statistics

Standard deviation2.3989651
Coefficient of variation (CV)1.4285932
Kurtosis29.850561
Mean1.67925
Median Absolute Deviation (MAD)1
Skewness4.5245704
Sum268.68
Variance5.7550334
MonotonicityNot monotonic
2023-04-07T04:10:49.771571image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 50
31.2%
0 37
23.1%
2 26
16.2%
3 12
 
7.5%
4 6
 
3.8%
0.5 6
 
3.8%
5 4
 
2.5%
6 3
 
1.9%
7 3
 
1.9%
1.5 2
 
1.2%
Other values (11) 11
 
6.9%
ValueCountFrequency (%)
0 37
23.1%
0.07 1
 
0.6%
0.1 1
 
0.6%
0.2 1
 
0.6%
0.3 1
 
0.6%
0.4 1
 
0.6%
0.45 1
 
0.6%
0.5 6
 
3.8%
1 50
31.2%
1.15 1
 
0.6%
ValueCountFrequency (%)
21 1
 
0.6%
14 1
 
0.6%
7 3
 
1.9%
6 3
 
1.9%
5 4
 
2.5%
4 6
 
3.8%
3 12
7.5%
2.43 1
 
0.6%
2 26
16.2%
1.58 1
 
0.6%

Time spend on Facebook? (In hours)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.281875
Minimum0
Maximum21
Zeros147
Zeros (%)91.9%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-04-07T04:10:49.867891image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum21
Range21
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.8158932
Coefficient of variation (CV)6.4421932
Kurtosis109.82226
Mean0.281875
Median Absolute Deviation (MAD)0
Skewness10.00041
Sum45.1
Variance3.2974682
MonotonicityNot monotonic
2023-04-07T04:10:49.952124image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 147
91.9%
1 6
 
3.8%
3 2
 
1.2%
2 2
 
1.2%
21 1
 
0.6%
8 1
 
0.6%
0.1 1
 
0.6%
ValueCountFrequency (%)
0 147
91.9%
0.1 1
 
0.6%
1 6
 
3.8%
2 2
 
1.2%
3 2
 
1.2%
8 1
 
0.6%
21 1
 
0.6%
ValueCountFrequency (%)
21 1
 
0.6%
8 1
 
0.6%
3 2
 
1.2%
2 2
 
1.2%
1 6
 
3.8%
0.1 1
 
0.6%
0 147
91.9%
Distinct15
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.743125
Minimum0
Maximum16
Zeros12
Zeros (%)7.5%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-04-07T04:10:50.049326image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile5
Maximum16
Range16
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.7798177
Coefficient of variation (CV)1.02105
Kurtosis26.169373
Mean1.743125
Median Absolute Deviation (MAD)0.8
Skewness3.9763807
Sum278.9
Variance3.1677512
MonotonicityNot monotonic
2023-04-07T04:10:50.154767image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 64
40.0%
2 34
21.2%
3 15
 
9.4%
0 12
 
7.5%
0.5 11
 
6.9%
4 7
 
4.4%
5 5
 
3.1%
0.3 3
 
1.9%
1.5 2
 
1.2%
0.1 2
 
1.2%
Other values (5) 5
 
3.1%
ValueCountFrequency (%)
0 12
 
7.5%
0.1 2
 
1.2%
0.3 3
 
1.9%
0.5 11
 
6.9%
1 64
40.0%
1.5 2
 
1.2%
2 34
21.2%
2.3 1
 
0.6%
3 15
 
9.4%
4 7
 
4.4%
ValueCountFrequency (%)
16 1
 
0.6%
8 1
 
0.6%
7 1
 
0.6%
6 1
 
0.6%
5 5
 
3.1%
4 7
 
4.4%
3 15
9.4%
2.3 1
 
0.6%
2 34
21.2%
1.5 2
 
1.2%
Distinct18
Distinct (%)11.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.954875
Minimum0
Maximum16
Zeros62
Zeros (%)38.8%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-04-07T04:10:50.275886image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum16
Range16
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.934675
Coefficient of variation (CV)2.0261029
Kurtosis40.286183
Mean0.954875
Median Absolute Deviation (MAD)1
Skewness5.7993424
Sum152.78
Variance3.7429673
MonotonicityNot monotonic
2023-04-07T04:10:50.382263image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0 62
38.8%
1 58
36.2%
2 9
 
5.6%
3 7
 
4.4%
0.5 7
 
4.4%
0.3 2
 
1.2%
4 2
 
1.2%
0.1 2
 
1.2%
1.5 2
 
1.2%
0.15 1
 
0.6%
Other values (8) 8
 
5.0%
ValueCountFrequency (%)
0 62
38.8%
0.01 1
 
0.6%
0.1 2
 
1.2%
0.15 1
 
0.6%
0.19 1
 
0.6%
0.2 1
 
0.6%
0.3 2
 
1.2%
0.33 1
 
0.6%
0.5 7
 
4.4%
0.6 1
 
0.6%
ValueCountFrequency (%)
16 1
 
0.6%
15 1
 
0.6%
8 1
 
0.6%
4 2
 
1.2%
3 7
 
4.4%
2 9
 
5.6%
1.5 2
 
1.2%
1 58
36.2%
0.6 1
 
0.6%
0.5 7
 
4.4%

Time spend on Reddit? (In hours)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
0
155 
1
 
3
2
 
1
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters160
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.2%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 155
96.9%
1 3
 
1.9%
2 1
 
0.6%
4 1
 
0.6%

Length

2023-04-07T04:10:50.491970image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-07T04:10:50.608950image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
0 155
96.9%
1 3
 
1.9%
2 1
 
0.6%
4 1
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 155
96.9%
1 3
 
1.9%
2 1
 
0.6%
4 1
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 155
96.9%
1 3
 
1.9%
2 1
 
0.6%
4 1
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 160
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 155
96.9%
1 3
 
1.9%
2 1
 
0.6%
4 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 155
96.9%
1 3
 
1.9%
2 1
 
0.6%
4 1
 
0.6%

Time spend on Discord? (In hours)
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size1.4 KiB

Time spend on Pinterest? (In hours)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.169375
Minimum0
Maximum4
Zeros134
Zeros (%)83.8%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-04-07T04:10:50.707051image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum4
Range4
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.47437438
Coefficient of variation (CV)2.8007344
Kurtosis27.405281
Mean0.169375
Median Absolute Deviation (MAD)0
Skewness4.3667572
Sum27.1
Variance0.22503105
MonotonicityNot monotonic
2023-04-07T04:10:50.806479image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 134
83.8%
1 20
 
12.5%
0.2 3
 
1.9%
4 1
 
0.6%
2 1
 
0.6%
0.5 1
 
0.6%
ValueCountFrequency (%)
0 134
83.8%
0.2 3
 
1.9%
0.5 1
 
0.6%
1 20
 
12.5%
2 1
 
0.6%
4 1
 
0.6%
ValueCountFrequency (%)
4 1
 
0.6%
2 1
 
0.6%
1 20
 
12.5%
0.5 1
 
0.6%
0.2 3
 
1.9%
0 134
83.8%

Time spend on Twitter? (In hours)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct10
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3485625
Minimum0
Maximum24
Zeros136
Zeros (%)85.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-04-07T04:10:50.913487image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.0789732
Coefficient of variation (CV)5.96442
Kurtosis109.40255
Mean0.3485625
Median Absolute Deviation (MAD)0
Skewness10.032882
Sum55.77
Variance4.3221294
MonotonicityNot monotonic
2023-04-07T04:10:51.007690image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 136
85.0%
1 13
 
8.1%
0.15 2
 
1.2%
0.5 2
 
1.2%
2 2
 
1.2%
0.27 1
 
0.6%
24 1
 
0.6%
10 1
 
0.6%
3 1
 
0.6%
0.2 1
 
0.6%
ValueCountFrequency (%)
0 136
85.0%
0.15 2
 
1.2%
0.2 1
 
0.6%
0.27 1
 
0.6%
0.5 2
 
1.2%
1 13
 
8.1%
2 2
 
1.2%
3 1
 
0.6%
10 1
 
0.6%
24 1
 
0.6%
ValueCountFrequency (%)
24 1
 
0.6%
10 1
 
0.6%
3 1
 
0.6%
2 2
 
1.2%
1 13
 
8.1%
0.5 2
 
1.2%
0.27 1
 
0.6%
0.2 1
 
0.6%
0.15 2
 
1.2%
0 136
85.0%
Distinct13
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.49125
Minimum0
Maximum24
Zeros131
Zeros (%)81.9%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-04-07T04:10:51.098923image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.4477017
Coefficient of variation (CV)4.9825989
Kurtosis63.809161
Mean0.49125
Median Absolute Deviation (MAD)0
Skewness7.6522795
Sum78.6
Variance5.9912437
MonotonicityNot monotonic
2023-04-07T04:10:51.203756image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 131
81.9%
1 16
 
10.0%
0.3 2
 
1.2%
0.5 2
 
1.2%
24 1
 
0.6%
15 1
 
0.6%
0.7 1
 
0.6%
12 1
 
0.6%
2 1
 
0.6%
4 1
 
0.6%
Other values (3) 3
 
1.9%
ValueCountFrequency (%)
0 131
81.9%
0.1 1
 
0.6%
0.2 1
 
0.6%
0.3 2
 
1.2%
0.5 2
 
1.2%
0.7 1
 
0.6%
1 16
 
10.0%
2 1
 
0.6%
3 1
 
0.6%
4 1
 
0.6%
ValueCountFrequency (%)
24 1
 
0.6%
15 1
 
0.6%
12 1
 
0.6%
4 1
 
0.6%
3 1
 
0.6%
2 1
 
0.6%
1 16
10.0%
0.7 1
 
0.6%
0.5 2
 
1.2%
0.3 2
 
1.2%

Overall time spent on other application? (In hours)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.295625
Minimum0
Maximum24
Zeros34
Zeros (%)21.2%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-04-07T04:10:51.428970image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.5
median1
Q33
95-th percentile8.1
Maximum24
Range24
Interquartile range (IQR)2.5

Descriptive statistics

Standard deviation3.3776242
Coefficient of variation (CV)1.471331
Kurtosis19.192472
Mean2.295625
Median Absolute Deviation (MAD)1
Skewness3.799733
Sum367.3
Variance11.408346
MonotonicityNot monotonic
2023-04-07T04:10:51.531695image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 39
24.4%
0 34
21.2%
2 27
16.9%
3 12
 
7.5%
4 11
 
6.9%
5 8
 
5.0%
0.5 7
 
4.4%
0.3 4
 
2.5%
10 3
 
1.9%
6 2
 
1.2%
Other values (11) 13
 
8.1%
ValueCountFrequency (%)
0 34
21.2%
0.2 1
 
0.6%
0.3 4
 
2.5%
0.5 7
 
4.4%
1 39
24.4%
1.4 1
 
0.6%
1.5 2
 
1.2%
2 27
16.9%
2.5 1
 
0.6%
3 12
 
7.5%
ValueCountFrequency (%)
24 1
 
0.6%
23 1
 
0.6%
12 2
 
1.2%
11 1
 
0.6%
10 3
 
1.9%
8 1
 
0.6%
7 1
 
0.6%
6 2
 
1.2%
5 8
5.0%
4 11
6.9%
Distinct18
Distinct (%)11.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.844375
Minimum0
Maximum16
Zeros3
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-04-07T04:10:51.624778image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q14
median8
Q314
95-th percentile16
Maximum16
Range16
Interquartile range (IQR)10

Descriptive statistics

Standard deviation5.0265552
Coefficient of variation (CV)0.56833357
Kurtosis-1.3110954
Mean8.844375
Median Absolute Deviation (MAD)4
Skewness0.049206675
Sum1415.1
Variance25.266257
MonotonicityNot monotonic
2023-04-07T04:10:51.717704image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
16 23
14.4%
10 16
10.0%
15 15
9.4%
4 14
8.8%
2 13
8.1%
12 12
7.5%
5 11
6.9%
8 10
 
6.2%
7 10
 
6.2%
6 9
 
5.6%
Other values (8) 27
16.9%
ValueCountFrequency (%)
0 3
 
1.9%
0.1 1
 
0.6%
1 3
 
1.9%
2 13
8.1%
3 7
4.4%
4 14
8.8%
5 11
6.9%
6 9
5.6%
7 10
6.2%
8 10
6.2%
ValueCountFrequency (%)
16 23
14.4%
15 15
9.4%
14 6
 
3.8%
13 1
 
0.6%
12 12
7.5%
11 1
 
0.6%
10 16
10.0%
9 5
 
3.1%
8 10
6.2%
7 10
6.2%
Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
No
79 
Maybe
62 
Yes
19 

Length

Max length5
Median length3
Mean length3.28125
Min length2

Characters and Unicode

Total characters525
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMaybe
2nd rowMaybe
3rd rowYes
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No 79
49.4%
Maybe 62
38.8%
Yes 19
 
11.9%

Length

2023-04-07T04:10:51.842048image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-04-07T04:10:51.973164image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
ValueCountFrequency (%)
no 79
49.4%
maybe 62
38.8%
yes 19
 
11.9%

Most occurring characters

ValueCountFrequency (%)
e 81
15.4%
N 79
15.0%
o 79
15.0%
M 62
11.8%
a 62
11.8%
y 62
11.8%
b 62
11.8%
Y 19
 
3.6%
s 19
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 365
69.5%
Uppercase Letter 160
30.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 81
22.2%
o 79
21.6%
a 62
17.0%
y 62
17.0%
b 62
17.0%
s 19
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
N 79
49.4%
M 62
38.8%
Y 19
 
11.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 525
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 81
15.4%
N 79
15.0%
o 79
15.0%
M 62
11.8%
a 62
11.8%
y 62
11.8%
b 62
11.8%
Y 19
 
3.6%
s 19
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 525
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 81
15.4%
N 79
15.0%
o 79
15.0%
M 62
11.8%
a 62
11.8%
y 62
11.8%
b 62
11.8%
Y 19
 
3.6%
s 19
 
3.6%
Distinct17
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.593125
Minimum0
Maximum15
Zeros4
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-04-07T04:10:52.076269image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.975
Q11
median2
Q33
95-th percentile6.1
Maximum15
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.2283796
Coefficient of variation (CV)0.85934138
Kurtosis8.0294363
Mean2.593125
Median Absolute Deviation (MAD)1
Skewness2.4384577
Sum414.9
Variance4.9656757
MonotonicityNot monotonic
2023-04-07T04:10:52.169446image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2 51
31.9%
1 43
26.9%
3 20
 
12.5%
4 13
 
8.1%
5 8
 
5.0%
6 5
 
3.1%
0 4
 
2.5%
8 3
 
1.9%
10 3
 
1.9%
1.3 2
 
1.2%
Other values (7) 8
 
5.0%
ValueCountFrequency (%)
0 4
 
2.5%
0.1 1
 
0.6%
0.2 1
 
0.6%
0.5 2
 
1.2%
1 43
26.9%
1.3 2
 
1.2%
1.5 1
 
0.6%
2 51
31.9%
2.5 1
 
0.6%
3 20
 
12.5%
ValueCountFrequency (%)
15 1
 
0.6%
11 1
 
0.6%
10 3
 
1.9%
8 3
 
1.9%
6 5
 
3.1%
5 8
 
5.0%
4 13
 
8.1%
3 20
 
12.5%
2.5 1
 
0.6%
2 51
31.9%
Distinct15
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.30125
Minimum0
Maximum15
Zeros22
Zeros (%)13.8%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-04-07T04:10:52.267147image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile6.2
Maximum15
Range15
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.4612976
Coefficient of variation (CV)1.0695481
Kurtosis7.9112989
Mean2.30125
Median Absolute Deviation (MAD)1
Skewness2.5011509
Sum368.2
Variance6.0579858
MonotonicityNot monotonic
2023-04-07T04:10:52.369064image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 50
31.2%
2 28
17.5%
3 23
14.4%
0 22
13.8%
4 15
 
9.4%
5 6
 
3.8%
10 6
 
3.8%
0.5 3
 
1.9%
2.5 1
 
0.6%
0.2 1
 
0.6%
Other values (5) 5
 
3.1%
ValueCountFrequency (%)
0 22
13.8%
0.2 1
 
0.6%
0.5 3
 
1.9%
1 50
31.2%
1.5 1
 
0.6%
2 28
17.5%
2.5 1
 
0.6%
3 23
14.4%
3.5 1
 
0.6%
4 15
 
9.4%
ValueCountFrequency (%)
15 1
 
0.6%
13 1
 
0.6%
10 6
 
3.8%
6 1
 
0.6%
5 6
 
3.8%
4 15
9.4%
3.5 1
 
0.6%
3 23
14.4%
2.5 1
 
0.6%
2 28
17.5%

Interactions

2023-04-07T04:10:44.207093image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:09.003867image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:21.252357image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
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2023-04-07T04:08:59.197297image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:12.322201image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:29.218128image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
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2023-04-07T04:10:45.853421image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:15.505852image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:29.013470image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:39.108372image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:45.880700image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:53.959687image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:05.958080image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:21.279601image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:33.704273image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:40.994761image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:48.309102image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:57.811303image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:10.051087image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:25.932463image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:38.967874image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:46.003802image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:16.722785image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:30.473150image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:39.714790image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:46.657200image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:55.196834image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:07.454739image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:23.102761image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:34.445114image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:41.704726image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:49.246299image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:58.916634image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:11.672818image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:27.649622image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:40.002548image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:46.145118image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:18.273655image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:32.211918image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:40.522253image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:47.564816image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:56.504996image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:09.157954image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:25.206956image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:35.388763image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:42.598325image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:50.340401image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:00.277257image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:13.451659image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:29.635032image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:41.257546image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:46.287773image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:19.998563image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:34.178451image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:41.613787image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:48.645694image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:57.901605image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:10.997106image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:27.614641image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:36.547252image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:43.750079image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:51.633676image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:01.787836image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:15.411659image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:32.058058image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:42.920028image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:46.419648image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:21.049127image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:35.405430image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:42.358390image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:49.348995image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:08:58.887538image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:12.129214image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:28.973576image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:37.274337image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:44.489634image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:09:52.444850image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:02.711474image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:16.622503image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:33.558859image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
2023-04-07T04:10:43.991304image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/

Correlations

2023-04-07T04:10:52.511679image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Enter Marks(percentage) For 10th Grade:Enter Marks (percentage) For Previous Semester:How often do you use social media ? (In hours)Time spent on WhatsApp? (In hours)Time spend on Instagram? (In hours)Time spend on Facebook? (In hours)Time spend on YouTube? (In hours)Time spend on Snapchat? (In hours)Time spend on Pinterest? (In hours)Time spend on Twitter? (In hours)Time spend on Telegram? (In hours)Overall time spent on other application? (In hours)What is the maximum time that you have spent away from your phone? (In hours)Entertainment usage time while using phone(per day) (In hours)Productivity and finance time while using phone (per day)(In hours)Department:Choose Current year:According to you, what need does social media fulfill?How many social media platforms are you on?Time spend on Reddit? (In hours)Do you consider yourself to be addicted to social media?
Enter Marks(percentage) For 10th Grade:1.0000.4460.1770.2570.045-0.011-0.002-0.0530.0420.051-0.0830.015-0.2170.0160.1600.5130.4050.0000.0000.0000.000
Enter Marks (percentage) For Previous Semester:0.4461.0000.1900.129-0.0070.057-0.098-0.0100.1060.094-0.0460.006-0.0900.0900.2020.1840.1390.0000.0000.0000.000
How often do you use social media ? (In hours)0.1770.1901.0000.1540.4410.0570.2240.2600.2280.0470.0020.074-0.1700.4860.1800.0620.0210.1260.0420.0000.247
Time spent on WhatsApp? (In hours)0.2570.1290.1541.0000.2110.2290.2870.2900.1170.015-0.0200.108-0.1050.1480.1500.0000.2310.0080.3900.1790.080
Time spend on Instagram? (In hours)0.045-0.0070.4410.2111.0000.2560.1050.4440.3060.1070.0330.024-0.1580.4810.2300.1890.1540.0000.3870.0360.159
Time spend on Facebook? (In hours)-0.0110.0570.0570.2290.2561.0000.1800.2480.1870.3350.3690.213-0.2210.2180.0690.0000.0760.0000.6670.0000.000
Time spend on YouTube? (In hours)-0.002-0.0980.2240.2870.1050.1801.0000.1820.0170.1430.1100.2080.0050.2340.2390.0000.1620.0000.3660.3820.175
Time spend on Snapchat? (In hours)-0.053-0.0100.2600.2900.4440.2480.1821.0000.2420.1990.0650.1240.0120.2990.1440.1240.0460.0000.2440.4040.068
Time spend on Pinterest? (In hours)0.0420.1060.2280.1170.3060.1870.0170.2421.0000.3390.2380.092-0.0390.1990.1260.0000.2140.0000.4200.6680.101
Time spend on Twitter? (In hours)0.0510.0940.0470.0150.1070.3350.1430.1990.3391.0000.4320.210-0.0620.1390.1730.0000.0210.0000.5990.5660.178
Time spend on Telegram? (In hours)-0.083-0.0460.002-0.0200.0330.3690.1100.0650.2380.4321.0000.265-0.0410.0620.0830.1350.0800.0000.4330.3790.000
Overall time spent on other application? (In hours)0.0150.0060.0740.1080.0240.2130.2080.1240.0920.2100.2651.0000.0570.2170.0040.1050.0600.0930.5120.4090.208
What is the maximum time that you have spent away from your phone? (In hours)-0.217-0.090-0.170-0.105-0.158-0.2210.0050.012-0.039-0.062-0.0410.0571.000-0.1790.1330.0790.0000.0000.0650.0000.104
Entertainment usage time while using phone(per day) (In hours)0.0160.0900.4860.1480.4810.2180.2340.2990.1990.1390.0620.217-0.1791.0000.2740.0000.0000.0000.3520.1110.355
Productivity and finance time while using phone\n(per day)(In hours)0.1600.2020.1800.1500.2300.0690.2390.1440.1260.1730.0830.0040.1330.2741.0000.0000.1020.0000.2210.1490.000
Department:0.5130.1840.0620.0000.1890.0000.0000.1240.0000.0000.1350.1050.0790.0000.0001.0000.5120.0910.2510.0000.000
Choose Current year:0.4050.1390.0210.2310.1540.0760.1620.0460.2140.0210.0800.0600.0000.0000.1020.5121.0000.2100.0000.0710.116
According to you, what need does social media fulfill?0.0000.0000.1260.0080.0000.0000.0000.0000.0000.0000.0000.0930.0000.0000.0000.0910.2101.0000.1450.0000.025
How many social media platforms are you on?0.0000.0000.0420.3900.3870.6670.3660.2440.4200.5990.4330.5120.0650.3520.2210.2510.0000.1451.0000.7840.181
Time spend on Reddit? (In hours)0.0000.0000.0000.1790.0360.0000.3820.4040.6680.5660.3790.4090.0000.1110.1490.0000.0710.0000.7841.0000.106
Do you consider yourself to be addicted to social media?0.0000.0000.2470.0800.1590.0000.1750.0680.1010.1780.0000.2080.1040.3550.0000.0000.1160.0250.1810.1061.000

Missing values

2023-04-07T04:10:46.645059image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-04-07T04:10:47.207031image/svg+xmlMatplotlib v3.6.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Department:Choose Current year:Enter Marks(percentage) For 10th Grade:Enter Marks (percentage) For Previous Semester:How often do you use social media ? (In hours)According to you, what need does social media fulfill?How many social media platforms are you on?Time spent on WhatsApp? (In hours)Time spend on Instagram? (In hours)Time spend on Facebook? (In hours)Time spend on YouTube? (In hours)Time spend on Snapchat? (In hours)Time spend on Reddit? (In hours)Time spend on Discord? (In hours)Time spend on Pinterest? (In hours)Time spend on Twitter? (In hours)Time spend on Telegram? (In hours)Overall time spent on other application? (In hours)What is the maximum time that you have spent away from your phone? (In hours)Do you consider yourself to be addicted to social media?Entertainment usage time while using phone(per day) (In hours)Productivity and finance time while using phone (per day)(In hours)
0ComputerSecond year93.2080.6317.0Educational, Entertainment, Research/Reading, GamingWhatsApp, Instagram, YouTube, Snapchat1.02.00.00.01.0000.00.00.02.07.0Maybe2.01.0
1Information TechnologyFirst year85.0065.0010.0Educational, Entertainment, Research/Reading, GamingWhatsApp, Instagram, Facebook, YouTube, Snapchat, Discord, Twitter1.02.00.03.02.000.50.00.00.01.016.0Maybe4.03.0
2Information TechnologySecond year85.0063.0010.0Educational, Entertainment, Research/ReadingWhatsApp, Instagram, Facebook, YouTube, Snapchat, Discord, Twitter,3.07.00.05.01.0020.01.01.02.010.0Yes5.02.0
3Information TechnologySecond year62.0069.002.0EntertainmentWhatsApp, Instagram, YouTube, Snapchat, Discord, Pinterest1.03.00.02.01.0000.00.00.02.09.0No3.05.0
4ElectronicsThird year77.2081.672.0Educational, EntertainmentWhatsApp, YouTube, Snapchat, Pinterest, Twitter1.00.00.03.01.0000.01.00.01.016.0No2.01.0
5ElectronicsThird year72.0060.001.0Educational, Entertainment, Research/ReadingWhatsApp, Instagram, YouTube, Snapchat, Pinterest1.01.00.00.01.0000.00.00.00.06.0Maybe2.02.0
6Artificial IntelligenceThird year60.0060.000.0EntertainmentWhatsApp5.00.00.05.01.0000.00.00.011.011.0No11.00.0
7ElectronicsThird year57.0065.002.0Educational, Entertainment, GamingWhatsApp, Instagram, Facebook, YouTube, Snapchat, Telegram1.01.00.01.01.0000.00.01.03.010.0Maybe2.01.0
8ElectronicsThird year69.4075.280.0EducationalWhatsApp, YouTube, Snapchat,2.00.00.01.00.0000.00.00.01.015.0No1.01.0
9ElectronicsThird year59.7871.161.0EducationalWhatsApp, YouTube, Snapchat1.01.00.01.01.0000.00.00.04.015.0Maybe1.01.0
Department:Choose Current year:Enter Marks(percentage) For 10th Grade:Enter Marks (percentage) For Previous Semester:How often do you use social media ? (In hours)According to you, what need does social media fulfill?How many social media platforms are you on?Time spent on WhatsApp? (In hours)Time spend on Instagram? (In hours)Time spend on Facebook? (In hours)Time spend on YouTube? (In hours)Time spend on Snapchat? (In hours)Time spend on Reddit? (In hours)Time spend on Discord? (In hours)Time spend on Pinterest? (In hours)Time spend on Twitter? (In hours)Time spend on Telegram? (In hours)Overall time spent on other application? (In hours)What is the maximum time that you have spent away from your phone? (In hours)Do you consider yourself to be addicted to social media?Entertainment usage time while using phone(per day) (In hours)Productivity and finance time while using phone (per day)(In hours)
150ComputerThird year94.091.895.0EntertainmentWhatsApp, Instagram, YouTube, Snapchat, Pinterest3.01.000.01.01.00I don't use this Social media Application1.00.000.02.08.0No2.00.0
151ComputerThird year88.087.002.0EducationalWhatsApp, Instagram, YouTube, Snapchat2.02.000.02.01.0000.00.000.07.016.0No0.04.0
152ComputerThird year56.079.872.5Educational, Research/ReadingWhatsApp, Instagram, YouTube1.01.000.01.00.0000.00.000.01.015.0No2.02.0
153ComputerThird year85.086.002.0Educational, Entertainment, Research/Reading, GamingWhatsApp, Instagram, YouTube, Snapchat, Telegram,0.51.000.01.00.2000.00.000.51.012.0Maybe3.02.0
154ComputerThird year91.090.004.0Educational, Entertainment, Research/ReadingWhatsApp, Instagram, YouTube, Snapchat, Pinterest, Twitter, Telegram,2.02.000.01.01.0001.00.000.01.010.0No2.03.0
155ComputerThird year88.082.0012.0Educational, Entertainment, GamingWhatsApp, Instagram, Facebook, YouTube, Snapchat, Discord, Twitter, Telegram6.07.002.05.03.0011.01.003.04.012.0Maybe10.04.0
156ComputerThird year89.086.002.0EducationalWhatsApp, Instagram, YouTube, Snapchat, Pinterest1.00.450.03.01.000.32.00.150.24.016.0No1.04.0
157ElectronicsThird year63.869.682.0Entertainment, Research/ReadingWhatsApp, Instagram, YouTube, Snapchat1.01.000.04.00.0000.00.000.05.05.0No4.02.0
158ComputerThird year85.085.003.5EntertainmentWhatsApp, Instagram, YouTube, Snapchat, Reddit, Discord, Pinterest, Twitter, Telegram2.02.000.01.01.0110.50.500.53.03.0Maybe3.04.0
159ComputerThird year90.080.002.0Entertainment, Research/ReadingWhatsApp, Instagram, YouTube, Snapchat2.01.000.01.00.5000.00.000.01.516.0Maybe2.00.5